Triple
T19791735
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chinggis City |
E475426
|
entity |
| Predicate | hasNamedForReason |
P65844
|
FINISHED |
| Object | in honor of Genghis Khan |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: in honor of Genghis Khan | Statement: [Chinggis City, hasNamedForReason, in honor of Genghis Khan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNamedForReason Context triple: [Chinggis City, hasNamedForReason, in honor of Genghis Khan]
-
A.
hasNameGivenTo
Indicates that one entity is the name that has been assigned or given to another entity.
-
B.
usesNameDueTo
chosen
Indicates that one entity adopts or applies a particular name for another entity specifically because of some motivating reason, circumstance, or dependency.
-
C.
namedIn
Indicates that one entity is explicitly mentioned or referenced by name within another entity (such as a document, statement, or record).
-
D.
hasNaming
Indicates that one entity assigns, bears, or is associated with a specific name or designation provided by another entity.
-
E.
hasGivenNameTo
Indicates that one entity has assigned or provided a given (first) name to another entity.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d8e51b014081908b263e167370529a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e653c37a3c819080f195d58adaaa7b |
completed | April 20, 2026, 4:26 p.m. |
| PD | Predicate disambiguation | batch_69e5305858108190bbbfdb9ba3ab9f80 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:49 p.m.